Friday, 26 August 2016

A Wavelet Tour of Signal Processing: The Sparse Way by S. Mallat - 3rd Ed.

Book Description
The new edition of this classic book gives all the major concepts, techniques and applications of sparse representation, reflecting the key role the subject plays in today's signal processing. The book clearly presents the standard representations with Fourier, wavelet and time-frequency transforms, and the construction of orthogonal bases with fast algorithms. The central concept of sparsity is explained and applied to signal compression, noise reduction, and inverse problems, while coverage is given to sparse representations in redundant dictionaries, super-resolution and compressive sensing applications.

Table of Contents
CHAPTER 1 - Sparse Representations
CHAPTER 2 - The Fourier Kingdom
CHAPTER 3 - Discrete Revolution
CHAPTER 4 - Time Meets Frequency
CHAPTER 5 - Frames
CHAPTER 6 - Wavelet Zoom
CHAPTER 7 - Wavelet Bases
CHAPTER 8 - Wavelet Packet and Local Cosine Bases
CHAPTER 9 - Approximations in Bases
CHAPTER 10 - Compression
CHAPTER 11 - Denoising
CHAPTER 12 - Sparsity in Redundant Dictionaries
CHAPTER 13 - Inverse Problems

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Sunday, 21 August 2016

Beginning JSON by Ben Smith - Free PDF Download

Book Description
Beginning JSON is the definitive guide to JSON - JavaScript Object Notation - today’s standard in data formatting for the web. The book starts with the basics, and walks you through all aspects of using the JSON format. Beginning JSON covers all areas of JSON from the basics of data formats to creating your own server to store and retrieve persistent data. Beginning JSON provides you with the skill set required for reading and writing properly validated JSON data.

Table of Contents
Chapter 1: JavaScript Basics
Chapter 2: Special Objects
Chapter 3: String Manipulation
Chapter 4: Introducing JSON
Chapter 5: Creating JSON
Chapter 6: Parsing JSON
Chapter 7: Persisting JSON: I
Chapter 8: Data Interchange
Chapter 9: X-Origin Resources
Chapter 10: Serving JSON
Chapter 11: Posting JSON
Chapter 12: Persisting JSON: II
Chapter 13: Working with Templates
Chapter 14: Putting It All Together

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Higher Engineering Mathematics by Grewal B. S. 42th Ed.

Book Description
The book provides a clear exposition of essential tools of applied mathematics from a modern point of view and meets complete requirements of engineering and computer science students. Every effort has been made to keep the presentation at once simple and lucid. It is written with the firm conviction that a good book is one that can be read with minimum guidance from the instructor. To achieve this, more than the usual number of solved examples, followed by properly graded problems have been given. Many of the examples and problems have been selected from recent papers of various university and other engineering examinations. Basic Concepts and Useful Information has been given in an Appendix.

Table of Contents
-  Algebra & Geometry: Solution of equations, Linear algebra: Determinants, Matrices, Vector algebra and Solid geometry.
- Calculus: Differential calculus, Partial differentiation, Integral calculus, Multiple integrals, Vector calculus.
- Series: Infinite Series and Fourier Series.
- Differential Equations: Differential equations of first order and their applications, Linear differential equations and their applications, Differential equations of different types, Series solution of differential equations and special functions, Partial differential equations and their applications.
- Complex Analysisc: Complex numbers and functions, Calculus of complex functions.
- Transforms: Laplace Transforms, Fourier transforms and Z-transforms.
- Numerical Techniques: Empirical Laws and Curve fitting, Statistical methods, Probability and Distributions, Sampling and Inference, Numerical methods, Finite differences and Interpolation, Difference equations, Numerical solution of Ordinary and Partial differential equations, Linear programming.
- Special Topics: Calculus of variations, Integral equations, Discrete mathematics, Tensors.
- An exhaustive list of Objective Type of Questions has been given at the end of each chapter. Standard Tables, Answers to Problems, and a fairly comprehensive

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Monday, 25 July 2016

Digital Design: With an Introduction to the Verilog HDL by Morris Mano

Book Description
Digital Design, fifth edition is a modern update of the classic authoritative text on digital design.  This book teaches the basic concepts of digital design in a clear, accessible manner. The book presents the basic tools for the design of digital circuits and provides procedures suitable for a variety of digital applications.

Table of Contents
1 Digital Systems and Binary Numbers
2 Boolean Algebra and Logic Gates
3 Gate‐Level Minimization
4 Combinational Logic
5 Synchronous Sequential Logic
6 Registers and Counters
7 Memory and Programmable Logic
8 Design at the Register Transfer Level
9 Laboratory Experiments with Standard ICs and FPGAs
10 Standard Graphic Symbols

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Thursday, 21 July 2016

Machine Learning in Python: Essential Techniques for Predictive Analysis

Book Description
Machine Learning in Python shows you how to successfully analyze data using only two core machine learning algorithms, and how to apply them using Python. By focusing on two algorithm families that effectively predict outcomes, this book is able to provide full descriptions of the mechanisms at work, and the examples that illustrate the machinery with specific, hackable code. The algorithms are explained in simple terms with no complex math and applied using Python, with guidance on algorithm selection, data preparation, and using the trained models in practice. You will learn a core set of Python programming techniques, various methods of building predictive models, and how to measure the performance of each model to ensure that the right one is used. The chapters on penalized linear regression and ensemble methods dive deep into each of the algorithms, and you can use the sample code in the book to develop your own data analysis solutions.

Table of Contents
Chapter 1 The Two Essential Algorithms for Making Predictions
Chapter 2 Understand the Problem by Understanding the Data
Chapter 3 Predictive Model Building: Balancing Performance, Complexity, and Big Data
Chapter 4 Penalized Linear Regression
Chapter 5 Building Predictive Models Using Penalized Linear Methods
Chapter 6 Ensemble Methods
Chapter 7 Building Ensemble Models with Python

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Designing Machine Learning Systems with Python - Free PDF Download

Book Description
There are many reasons why machine learning models may not give accurate results. By looking at these systems from a design perspective, we gain a deeper understanding of the underlying algorithms and the optimisational methods that are available. This book will give you a solid foundation in the machine learning design process, and enable you to build customised machine learning models to solve unique problems. You may already know about, or have worked with, some of the off-the-shelf machine learning models for solving common problems such as spam detection or movie classification, but to begin solving more complex problems, it is important to adapt these models to your own specific needs. This book will give you this understanding and more.

Table of Contents
1. Thinking in Machine Learning
2. Tools and Techniques
3. Turning Data into Information
4. Models – Learning from Information
5. Linear Models
6. Neural Networks
7. Features – How Algorithms See the World
8. Learning with Ensembles
9. Design Strategies and Case Studies

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Building Machine Learning Systems with Python - Free PDF Download

Book Description
Master Machine Learning using a broad set of Python libraries and start building your own Python-based ML systems. Covers classification, regression, feature engineering, and much more guided by practical examples. A scenario-based tutorial to get into the right mind-set of a machine learner (data exploration) and successfully implement this in your new or existing projects.

Table of Contents
1. Getting Started with Python Machine Learning
2. Classifying with Real-world Examples
3. Clustering – Finding Related Posts
4. Topic Modeling
5. Classification – Detecting Poor Answers
6. Classification II – Sentiment Analysis
7. Regression
8. Recommendations
9. Classification – Music Genre Classification
10. Computer Vision
11. Dimensionality Reduction
12. Bigger Data

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Wednesday, 20 July 2016

Manufacturing Engineering and Technology - 6th and 7th Eds

Book Description
Manufacturing Engineering & Technology presents a mostly qualitative description of the science, technology, and practice of manufacturing. This includes detailed descriptions of manufacturing processes and the manufacturing enterprise that will help introduce students to important concepts.

Table of Contents
Part I: Fundamentals of Materials: Their Behavior and Manufacturing Properties
Part II: Metal-Casting Processes and Equipment
Part III: Forming and Shaping Processes and Equipment
Part IV: Machining Processes and Machine Tools
Part V: Micromanufacturing and Fabrication of Microelectronic Devices
Part VI: Joining Processes and Equipment
Part VII: Surface Technology
Part VIII: Engineering Metrology, Instrumentation, and Quality Assurance
Part IX: Manufacturing in a Competitive Environment

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